AI/machine learning
Best practices are not static; they evolve alongside advancements that redefine what is achievable.
New strides in computer vision, well controls indicators, and BOP alignment were showcased at the recent Offshore Technology Conference.
Gautam Swami, manager of corporate R&D at NOV and SPE member, shares his experiences in building a career in oil and gas R&D, discusses how innovation is shaping the industry, and offers guidance to young professionals.
-
This paper presents a family of machine-learning-based reduced-order models trained on rigorous first-principle thermodynamic simulation results to extract physicochemical properties. -
The authors of this paper describe a technology built on a causation-based artificial intelligence framework designed to forewarn complex, hard-to-detect state changes in chemical, biological, and geological systems.
-
Health, safety, and environment operations can be greatly enhanced by using artificial intelligence (AI) techniques on HSE data. One important aspect inherent in this process is the need to establish trust in the AI system among the users.
-
Registration is open for the SPE Europe Energy GeoHackathon, which will be held in October and November. It will be preceded by 4-week online bootcamp sessions on data science and geothermal energy, which will begin on 2 October.
-
This article presents the application of a reinforcement learning control framework based on the Deep Deterministic Policy Gradient. The crack propagation process is simulated in Abaqus, which is integrated with a reinforcement learning environment to control crack propagation in brittle material. The real-world deployment of the proposed control framework is also dis…
-
SPE and Project Innerspace are organizing the first Geothermal AInnovation Competition. Teams from around the world are invited to participate in this virtual competition aimed at showcasing the potential of AI-assisted work flows in the geothermal life cycle.
-
This paper describes a work flow that integrates data analysis, machine learning, and artificial intelligence to unlock the potential of large relative permeability databases.
-
The authors of this paper describe a solution using machine-learning techniques to predict sandstone distribution and, to some extent, automate the process of optimizing well placement.
-
With AI rapidly becoming a buzzword across industries, oil and gas companies are exploring ways to use this technology to fuel innovation in the energy sector.
-
Artificial intelligence (AI) tools have been used in geological survey methods for many years. Gaining insight into the scale and trends of this implementation could assist surveyors in making informed decisions about buying or developing new technologies.
